Lessons from the genomes of extremely acidophilic bacteria and archaea with special emphasis ...

16 Pages·2010·0.89 MB·English

ApplMicrobiolBiotechnol(2010)88:605–620
DOI10.1007/s00253-010-2795-9
MINI-REVIEW
Lessons from the genomes of extremely acidophilic
bacteria and archaea with special emphasis
on bioleaching microorganisms
JuanPabloCárdenas&JorgeValdés&RaquelQuatrini&
Francisco Duarte&David S. Holmes
Received:30June2010/Revised:22July2010/Accepted:22July2010/Publishedonline:10August2010
#Springer-Verlag2010
Abstract This mini-review describes the current status of investigation of major evolutionary trends that shape
recentgenomesequencingprojectsofextremelyacidophilic genomearchitectureandevolution.Despitethesepromising
microorganisms and highlights the most current scientific beginnings, a major conclusion is that the genome projects
advances emerging from their analysis. There are now at help focus attention on the tremendous effort still required
least 56 draft or completely sequenced genomes of acid- to understand the biological principles that support life in
ophilesincluding30bacteriaand26archaea.Therearealso extremely acidic environments, including those that might
complete sequences for 38 plasmids, 29 viruses, and allow engineers to take appropriate action designed to
additional DNA sequence information of acidic environ- improve the efficiency and rate of bioleaching and to
ments is available from eight metagenomic projects. A protect the environment.
special focus is provided on the genomics of acidophiles
fromindustrialbioleachingoperations.Itisshownhowthis Keywords Acidophiles.Genomics.Bioinformatics.
initial information provides a rich intellectual resource for Metabolic reconstruction.Ecophysiology
microbiologists that has potential to open innovative and
efficientresearchavenues.Examplespresentedillustratethe
useofgenomicinformationtoconstructpreliminarymodels Initial considerations
of metabolism of individual microorganisms. Most impor-
tantly, access to multiple genomes allows the prediction of We define “extreme acidophiles” as those organisms
metabolic and genetic interactions between members of the whose growth optimum is < pH3. At present, genomic
bioleaching microbial community (ecophysiology) and the information is available only for bacteria and archaea,
although eukaryotic microorganisms are abundant in
: : : : some acidophilic environments (Johnson 2008; Baker et al.
J.P.Cárdenas J.Valdés R.Quatrini F.Duarte
D.S.Holmes(*) 2009; Cid et al. 2010).
CenterforBioinformaticsandGenomeBiology, Bioleaching (or biomining) refers to the use of micro-
FundaciónCienciaparalaVida, organisms to solubilize metals, principally copper, from
Avda.Zanartu1482,
ores (Rawlings and Johnson 2007). Bioleaching occurs in
Santiago,Chile
heaps of crushed ore. A related process, termed biooxida-
e-mail:[email protected]
tion, takes place in stirred reactors and is used principally
: : :
J.P.Cárdenas J.Valdés F.Duarte D.S.Holmes for the recovery of gold (Rawlings and Johnson 2007).
Depto.deCienciasBiológicas,FacultaddeCienciasBiológicas,
Both bioleaching and biooxidation use many similar
UniversidadAndrésBello,
microorganisms, and both can potentially result in the
Santiago,Chile
production of acid mine drainage (AMD). Acid rock
PresentAddress: drainage(ARD)issimilartoAMD,butresultsfromnatural
J.Valdés
processes (e.g., thermal acid springs). The genomics of
ComputationalGenomicsLaboratory,CenterforBioinformatics
bacteria and archaea from both man-made and natural
andMolecularSimulations,UniversidaddeTalca,
Santiago,Chile acidic environments will be considered in this review,
606 ApplMicrobiolBiotechnol(2010)88:605–620
although the principle thrust will be on bioleaching characteristics (Fe(II) oxidation, sulfur oxidation, Fe(III)
environments. Principles that emerge from this focus on reduction, N fixation, nitrate reduction, presence of
2
bioleaching might be applicable, at least in part, to an flagellum, type of tricarboxylic acid cycle (TCA) cycle,
understanding of the biology of biooxidation, AMD and -trophy and CO fixation) for 26 bacterial genomes,
2
ARD (and vice versa). predicted from an analysis of the respective genomes. This
This mini-review focuses on work that uses genomics, sums to a total of 234 descriptive features (26 genomes ×
bioinformatics, and “omics” derivatives (transcriptomics, nineproperties).However,inspectionofTable1showsthat
proteomics, metagenomics, etc.) as the principal sources of 91 or 39% of these features remain to be evaluated (shown
information. Information has also been included that is by “?” in Table 1). These lacunae need to be filled.
derived from a fusion of omics approaches with experi- Obviously, there are many additional metabolic properties
mentally oriented research. However, papers that describe not presented in the Tables that can be predicted from the
almost exclusively experimental results have not been existinggenomedatabut,asyet,havenotbeendetermined.
evaluated. Many important literature citations are not Second, considerably more microbial diversity is now
reported in this mini-review, and attention is drawn to recognizedthanwasapparentininitialsurveysofbioleach-
other reviews where the missing information can be found ingheapsandotheracidicenvironments(Demergassoetal.
(Valenzuela et al. 2006; Holmes and Bonnefoy 2007; 2010; González-Toril et al. 2010). For example, a recent
Quatrini et al. 2007c; Jerez 2008; Siezen and Wilson study of the variation of 16S rRNA gene sequences of
2009; Bonnefoy 2010). Acidimicrobiumspp.revealedextensivestrainvariationthat
wassosubstantialthatitmightincludenewspeciesoreven
new genera (Schippers et al. 2010). In addition, classical
Lots of genomes, but are they sufficient? techniques of microbial identification can significantly
underestimate the true genetic diversity even within a
The first sequenced genome of an extreme acidophile was species. For example, although 100% identical at the 16S
the bioleaching γ-proteobacterium Acidithiobacillus fer- rRNA gene sequence level, two strains of A. ferrooxidans
rooxidans ATCC 23270 published in draft form over a have 16% difference in their gene content (Valdés et al.
decade ago (Selkov et al. 2000). There are now at least 56 2010). Clearly, a metagenomic and/or metatranscriptomic
genomes of extreme acidophiles completed or in progress approach would help assess the genetic variability present
with representatives of bacteria (30 genomes, Tables 1 and during bioleaching. Although several such cultivation-
3) and archaea (26 genomes, Tables 2 and 3). There are independent projects have been carried out on AMD, none
also eight metagenome projects of extremely acidic have evaluated the composition and/or dynamics of
environments, four of which are associated with the bioleaching consortia.
AMD of Iron Mountain. The latter provide sufficient It is also unlikely that the full range of bioleaching
metagenomicsequencecoveragetodescribedraftgenomes habitats has been sampled for microbial diversity, especial-
of four bacterial and nine archaeal species (Table 3). In ly if one considers the spatial and temporal variations
addition, complete sequences have been determined for 38 known to occur in bioleaching heaps and the significant
plasmids (Table 4) and 29 viruses (Table 5) from acidic variety of mineral substrates being bioleached in different
environments. parts of the world, all of which contribute to the
Representatives of psychrotolerant, mesophilic, moder- diversification of habitat. There are likely to be many
atelythermophilicandthermophilicmicroorganisms Gram- discoveries in the future of novel microorganisms that
positiveandGram-negativebacteria andarchaeahavebeen contribute to bioleaching.
or are being sequenced, providing a first glimpse of the Another issue of concern is that many genome sequenc-
genomics of acidophilic life over a range of environmental ing projects were carried out on strains that had been
conditions. An important question is whether this genome maintained in the laboratory, some for decades, allowing
information is sufficient to provide a reasonably complete thepotential accumulation ofgeneticmodifications suchas
descriptionofthegenomiccomplexityand,byinference,of genome rearrangements, mutations and gene loss. For
the full metabolic potential present in bioleaching oper- example,A.ferrooxidansATCC19859isknowntopossess
ations. It is suggested that the answer to this question is transposable elements in which mobilization in laboratory
“no” for two major reasons. growthconditionsaffectgenotypeandphenotype(Cabrejos
First, it is clear that the currently available genomic et al. 1999). However, several of the new genome projects,
information has been significantly underexploited as a for example those currently underway at the BHPB-FCV-
resource for information, and there is much more that can UCN, Biosigma and others listed as “personal communica-
be squeezed from the existing data. For example, Table 1 tion” (see Tables 1 and 2), describe microorganisms that
showsthepresenceorabsenceofninemetabolicfeaturesor have been isolated directly from bioleaching heaps with
ApplMicrobiolBiotechnol(2010)88:605–620 607
pathwayorfeatureabsent,?noinformationavailable.TheNCBIaccessionnumberis“”HhorseshoeincompleteTCAcycle,RreductivecompleteTCAcycle,Coxidativeoph,FAfacultativeautotroph,Amobligatemethylotroph,andOAobligateautotroph);natepathway,DSMZGermanResourceCentreforBiologicalMaterial,JCVIJ.CraigBHPBBHPBilliton,FCVFundaciónCienciaparalaVida,Chile;UCNUniversidad
featurepresent,whitemetabolicunpublisheddatafromtheFCV,whereMHmixotroph,Hheterotrm3HPmodified3-hydroxypropioKUUniversityofCopenhagen,Hawaii
Table1Draftinprogressandcompleteacidophilicbacterialgenomes Genomesarelinkedtometabolicinformation:blackmetabolicpathwayorprovidedwhenavailableexceptFP475956(EMBLaccessionnumber).GcompleteTCAcycle,IincompletepredictedTCAcycle,trophylifestyle(CBBCalvinBashamBensoncycle,rTCAreversetricarboxilicacidcycle,VenterInstitute,DOEDepartmentofEnergy,JGIJointGenomeInstitute,CatólicadelNorte,Chile;UCUniversityofCalifornia,UHUniversityof
608 ApplMicrobiolBiotechnol(2010)88:605–620
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610 ApplMicrobiolBiotechnol(2010)88:605–620
Table 4 Completely sequenced
plasmidsfromacidophilic Plasmid Organism Accession
environments
pTcM1 AcidithiobacilluscaldusMNG1 NC_010600
pTC-F14 AcidithiobacilluscaldusF NC_004734
pACRY01-08(8plasmids) AcidiphiliumcryptumJF-5 NC_009467-NC_009474
pTF5 AcidithiobacillusferrooxidansATCC33020 NC_005023
pTF4.1 AcidithiobacillusferrooxidansMAL4-1 NC_005120
pAACI01 AlicyclobacillusacidocaldariusDMS446 NC_013206
pAACI03 AlicyclobacillusacidocaldariusDMS446 NC_013208
p49879.1 LeptospirillumferrooxidansATCC49879 NC_006907
p49879.2 LeptospirillumferrooxidansATCC49879 NC_006909
pNOB8 Sulfolobussp.NOB8H2 NC_006493
pYN01 SulfolobusislandicusY.N.15.51 NC_012624
pLD8501 SulfolobusislandicusL.D.8.5 NC_013770
pXZ1 SulfolobusislandicusARN3/6 NC_010365
pSOG1 SulfolobusislandicusSOG2/4 NC_010597
pSOG2 SulfolobusislandicusSOG2/4 NC_010598
pSSVx SulfolobusislandicusRey15/4 NC_010011
pHVE14 Sulfolobusislandicus,strainsfromIceland NC_006425
pARN3 Sulfolobusislandicus,strainsfromIceland NC_006423
pARN4 Sulfolobusislandicus,strainsfromIceland AJ748323
pKEF9 Sulfolobusislandicus,strainsfromIceland NC_006422
pING1 SulfolobusislandicusHEN2P2 NC_004852
pRN1 SulfolobusislandicusREN1H1 NC_001771
pRN2 SulfolobusislandicusREN1H1 NC_002101
pHEN7 SulfolobusislandicusHEN7H2 NC_004853
pORA1 Sulfolobusneozealandicus NC_006906
pSSVi SulfolobussolfataricusP2 NC_013777
pIT3 SulfolobussolfataricusIT3 NC_005907
pTC Sulfolobustengchongensis NC_005969
pTA1 ThermoplasmaacidophilumH0-122 NC_008318
(tobenamed) SulfobacillusthermotoleransY0017 D.Rawlings,pers.comm
(tobenamed) SulfobacillusthermotoleransL15 D.Rawlings,pers.comm
minimal culturing and therefore have had less time to ofacompleteTCAcycleandtypeofCO fixationpathway
2
accumulate genetic changes post-isolation. (Tables1,2and3).Informationregardingthesemodelscan
In spite of these caveats, a deeper understanding of the be found in the principal publication describing the
microbial assemblages, their gene pools, and metabolic respective genome (Tables 1, 2 and 3) and references
potential in bioleaching operations is beginning to emerge therein. Some additional unpublished information is also
from genomics. Future work in this area is likely to be provided in Tables 1, 2 and 3. Some of the models listed
accelerated as the cost of DNA sequencing continues to have received experimental support, but clearly, additional
decline and new high throughput technologies are devel- experimentation is needed in many cases to validate the
oped (Eid et al. 2009; Ozsolak et al. 2009). bioinformatic predictions.
Metabolic models Unlocking the secrets of acidophilic proteins
Metabolic models have been derived from bioinformatic Mechanisms of pH homeostasis used by acidophiles to
interpretationofthegenomesequencesforFe(II)oxidation, maintain their intracellular pH around neutral have been
sulfur oxidation, Fe(III) reduction, N fixation, nitrate recently reviewed (Dopson 2010). However, little informa-
2
reduction, flagellum formation and the presence/absence tion is available concerning the mechanisms that proteins
ApplMicrobiolBiotechnol(2010)88:605–620 611
Table 5 Completely sequenced
virusesfromacidophilic Virus Host Accession
environments
Bottle-shapedvirus Acidianussp. NC_009452
Filamentousvirus1 Acidianussp. NC_005830
Filamentousvirus2 Acidianussp. NC_009884
Filamentousvirus3 Acidianussp. NC_010155
Filamentousvirus6 Acidianussp. NC_010152
Filamentousvirus7 Acidianussp. NC_010153
Filamentousvirus8 Acidianussp. NC_010154
Filamentousvirus9 Acidianussp. NC_010537
Rod-shapedvirus1 Acidianussp. NC_009965
Spindle-shapedvirus1 Acidianussp. NC_013585
Two-tailedvirus Acidianussp. NC_007409
AMDV1 LeptospirillumgroupsIIandIII Dicketal.(2009)
AMDV2 E-plasma(Thermaplasmatales) Dicketal.(2009)
AMDV3 A-/E-/G-plasma(Thermaplasmatales) Dicketal.(2009)
AMDV4 E-plasma(Thermaplasmatales) Dicketal.(2009)
AMDV5 I-plasma(Thermaplasmatales) Dicketal.(2009)
Virus1 Sulfolobussp. NC_001338
Virus2 Sulfolobussp. NC_005265
Filamentousvirus Sulfolobusislandicus NC_003214
Rod-shapedvirus1 Sulfolobusislandicus NC_004087
Rod-shapedvirus2 Sulfolobusislandicus NC_004086
Spindle-shapedvirus4 Sulfolobussp. NC_009986
Spindle-shapedvirus5 Sulfolobussp. NC_011217
Spindle-shapedvirus6 Sulfolobussp. NC_013587
Spindle-shapedvirus7 Sulfolobussp. NC_013588
Turretedicosahedralvirus Sulfolobussp. NC_005892
Kamchatka1virus Sulfolobussp. NC_005361
RaggedHillsvirus Sulfolobussp. NC_005360
STSV1virus Sulfolobustengchongensis NC_006268
use to correctly fold, make protein–protein contact and teins. However, only a few enzymes (extremozymes)
maintain function at very low extracellular pH values. This (Dopson 2010) and one electron transfer protein (Yamada
would include proteins located in the periplasm, outer et al. 2004) from extreme acidophiles have been used or
membraneandthosethatareexcretedoutsidethecellorare havebeenproposedforuseinbiotechnologicalapplications.
embeddedinthecytoplasmicmembranebuthavefoldsthat The predicted proteomes of extreme acidophiles provide
extrudeintotheperiplasm.Theseissuesarebeginningtobe a rich, but largely unexploited, hunting ground for proteins
addressed using genome sequence data to evaluate the that might have useful functions in biotechnological
proteomes of acidophiles (Bouchal et al. 2006) to predict applications.
subcellular locations (Chi et al. 2007) and to assess protein
folding in acidic conditions (Kanao et al. 2010). Also,
molecular modeling and simulation processes can predict Comparative genomics can generate models
single protein physicochemical and folding differences of the ecophysiology of acidic environments
between acidophilic and neutrophilic orthologs and can
suggesthowmembranetransportersofacidophilesfunction Over a decade ago, investigations began to reveal the
when confronted by a ΔpH of about 6 or 7 orders of complex interactions between microbes inhabiting natural
magnitude across the periplasmic membrane (pH6.5 inside and man-made acidic environments (Johnson 1998; Baker
to < pH1 outside) (Duarte et al. 2009). and Banfield 2003). Recent genomic-based analyses of
Many acidophiles are also thermophiles and their virtual acidophilic microbes have revealed further insight into the
proteomes could suggest useful thermo–acido stable pro- metabolic capabilities and the potential interactions that
612 ApplMicrobiolBiotechnol(2010)88:605–620
shape these microbial communities, in particular, those The ability to develop predictive models of interactions
related to bioleaching (Barreto et al. 2003; Osorio et al. in bioleaching communities, albeit in its infancy, is
2008a; Valdés et al. 2008a, b, 2010). Also, a number of arguably the most important contribution that can result
studies on the composition, structure and function of from an analysis of the genetic and metabolic potential of
extreme acidic aerial (Gonzalez-Toril et al. 2003; Garrido multiple genomes.
etal.2008)and subaerial streams(Tysonetal.2004;Allen
andBanfield2005;Rametal.2005;WhitakerandBanfield
2006; Allen et al. 2007; Lo et al. 2007; Andersson and Genomics predicts multiple pathways for CO fixation
2
Banfield 2008;Simmonset al.2008; Goltsman et al.2009; in bioleaching microorganisms
VerBerkmoes et al. 2009; Denef et al. 2010a) have
contributed to our understanding of the ecophysiology of Having so many genome sequences available has changed
biofilm-based AMD communities. The use of genomics- our perspective of the complexity of pathways that
enabled methods to study communities with reduced levels bioleaching microorganisms use to fix CO . Although the
2
of species richness, such as those found in the Iron Calvin cycle still appears to be the principal CO fixation
2
Mountain AMD, has resulted in a better understanding of process at ambient temperatures, it is now clear that other
the metabolic networks and evolutionary processes that CO fixation pathways such as the reverse TCA cycle and
2
operate within them. In such defined model systems, the the modified 3-hydroxypropionate pathway come into play
molecular and evolutionary base for ecological patterns (Tables 1 and 2) and eventually dominate as bioleaching
havebeguntoemerge,notonlyfacilitatingtheconstruction proceeds and temperatures rise in the heaps (Valdés et al.
of predictive ecosystem models but also uncovering 2010). It is important to deepen our knowledge of these
principles that may explain behavior in more complex additional routes and evaluate the role that they play in
systems (Denef et al. 2010b; Mueller et al. 2010) permitting thermophilic microbial consortia to fix CO in
2
During bioleaching, the composition of the microbial bioleaching dumps. A fourth pathway for CO fixation has
2
consortia changes over time as the bioleaching heap recently been described in members of the anaerobic
undergoes, among other changes, a temperature increase Archaeal Desulfurococcales and Thermoproteales families
from ambient temperature to about 70–80 °C due to (Berg et al. 2010b). Genomes of acidophiles can now be
exothermic oxidation reactions. Initially, mesophilic (20– searchedforgenespotentiallyencodingthisnovelpathway.
40 °C) consortia rich in bacteria dominate, but as bioleach- Increasing knowledge of pathways for fixing CO is
2
ingproceeds,thesemicrobialcommunitiesarereplacedfirst helping to build models for how carbon fixation might
by moderately thermophilic (40–55 °C) consortia, and haveevolvedinearlylife(Bergetal.2010a).Thestudyof
finally by extremely thermophilic (55–80 °C) consortia chemolithoautotrophs has played a particularly important
dominated by Archaea (Rawlings and Johnson 2007). It is role in the development of such models, for example, the
important to know the composition and activity of these iron–sulfur theory of the origin of life is based on the
evolving consortia in order to develop a better understand- structural and catalytic similarity of their mineral sub-
ing of the biology of bioleaching. Predictions of metabolic strates (e.g., pyrite, FeS ) with the catalytic Fe–S centers
2
potential from genomic data allow preliminary models of of many enzymes and cofactors of chemolithoautotrophs
theecophysiologyofsuchconsortiatobebuiltthatbeginto (Wächtershäuser 1988, 2007).
address questions such as who is capable of doing what, to
whom, where, when and under what circumstances. For
example, genome sequence information provides a catalog The incomplete TCA cycle is a hallmark of obligate
of the diverse pathways used by bioleaching autotrophs to autotrophy in acidophiles
obtain fixed carbon and suggests which autotrophs are
providing fixed carbon to the heterotrophs at the different It has been suggested that the absence of genes encoding
stages of bioleaching (Valdés et al. 2010). the irreversible oxidative α-ketoglutarate dehydrogenase
Inspection of Tables 1, 2 and 3 permits similar complex in the TCA cycle is a hallmark of obligate
predictions to be made regarding who are the primary autotrophy (Wood et al. 2004). The lack of this complex
fixers of atmospheric N in the bioleaching consortia, as results in an incomplete TCA cycle or a so-called TCA
2
has been done for the Iron mountain AMD community “horseshoe” in which pyruvate can be used as a source to
(Tyson et al. 2004). It is envisioned that a more detailed reoxidize NADH (oxidative branch) and for the formation
understanding of the ecophysiology could indicate if the of the biosynthetic precursor molecules citrate and a-
relationships between microorganisms, for example, be- ketoglutarate. Published information derived from genome
tween autotroph and heterotroph, are beneficial or detri- projects supplemented with unpublished data indicates that
mental to the bioleaching process. the horseshoe TCA cycle is found in obligate autotrophic
ApplMicrobiolBiotechnol(2010)88:605–620 613
acidophilic bacteria that use the Calvin cycle to fix CO phenomena,suchasbacterialrecognitionandattachmentto
2
(labeled“H”intheTCAcyclecolumnofTable1).Obligate specific mineral surfaces and biofilm formation. These
autotrophic bacteria that use the reverse TCA cycle to fix areas are crucial for understanding the bioleaching process.
CO also lack the α-ketoglutarate dehydrogenase complex Whereas advances in understanding motility, chemotaxis
2
in their TCA cycle. However, they are predicted to contain and biofilm formation in bioleaching microorganisms have
genes encoding a reversible 2-oxoacid: ferredoxin oxidore- beenmadethroughexperimentalapproaches,littlehasbeen
ductasecomplexthatcouldassumetheresponsibilityofthe done to data mine the genome sequences for novel
missing α-ketoglutarate dehydrogenase complex (labeled information. Bioinformatic models with supporting exper-
“R” in the TCA cycle column of Tables 1, 2 and 3). All imental evidence have been developed for biofilm forma-
sequenced acidophilic Archaea also use a reversible 2- tion (Barreto et al. 2005a, b) and quorum sensing (Farah et
oxoacid: ferredoxin oxidoreductase complex, but other al. 2005; Rivas et al. 2005, 2007; Soulère et al. 2008;
steps in their TCA cycle are also thought to be absent Castro et al. 2009) in a few bioleaching microorganisms.
(labeled“I”intheTCAcyclecolumnofTables1,2and3). Also, predictions have been made for the presence of
The presence or absence of genes for specific steps in the flagella genes (Tables 1, 2 and 3). However, it is clear that
TCA cycle/horseshoe could help predict obligate autotro- currentgenomesequenceinformationisunderexploitedasa
phy in novel microbial genomes. resource for advancing our understanding in this important
area.
Genomics proposes models for anaerobic respiration
Metalomics
Industrial bioleaching operations pump air into the biol-
eaching heap, providing oxygen and CO to support The study of metal resistance in biomining bacteria using
2
microbial growth. However, anaerobic conditions are genome data and bioinformatics is another area that is
known to occur in zones in bioleaching heaps where the relatively under-exploited. It is known that acidophiles are
air has not permeated or where intense microbial activity extremely resistant to a number of metals and metalloids
has resulted in the production of microaerophilic condi- compared to their neutrophilic counterparts, and mecha-
tions. Whereas considerable information is available nisms that potentially account for this resistance have
describing the oxidation reactions that support microbial recently been reviewed (Dopson 2010). However, no
growth in bioleaching heaps, less is known about the large-scale genomic comparison of metal resistance has
enzymes and electron transport pathways involved in been undertaken in acidophiles. Such a study might reveal
anaerobic or microaerophilic growth. Metagenomic and the presence of global mechanisms employed by acid-
genomicdataarebeginningtobeexploitedtopredictnovel ophiles,aswellassupplement ourknowledgeofgenesand
candidate genes and inferred enzymes and electron trans- pathways involved in resistance to high levels of mercury,
port pathways that might be used in anaerobiosis. For arsenic, copper, iron, etc.
example,potentialanaerobicpathwayshavebeenidentified Nearly a decade ago, genomeinformation was exploited
inmicroorganismsthathavebeendemonstratedexperimen- to predict metal resistance genes in A. ferrooxidans
tally to grow anaerobically using Fe(III) or nitrate as final (Holmes et al. 2001). A bioinformatic and experimental
electron acceptors (Tables 1, 2, and 3). Genomics also analysisofironhomeostasisanditspotentialregulationhas
permits the prediction of anaerobic growth for new been conducted for A. ferrooxidans (Quatrini et al. 2004,
genomes and metagenomes, for example: Leptospirillum 2005a, b, 2007b), including predictions and experimental
ferrodiazotrophum, L. ferrooxidans, L. rubarum, and validation of binding sites for the master iron regulator Fur
Leptospirillum sp. “5way CG” (using Fe(III)) (Goltsman andthepredictionofthegeneclustersthatitmightregulate
et al. 2009) and Thiomonas intermedia K-12 (unpublished) (Quatrinietal.2007a).Thesedatapermittheelaborationof
andThiomonassp.3A(usingnitrate)(Arsène-Ploetzeetal. integrated regulatory mechanisms and provide a wider
2010) (see Tables 1, 2, and 3). overview of how these specific functions could be
connected in a major regulatory plan. A bioinformatic
analysis of iron uptake and homeostasis has recently been
Genomic predictions for motility, chemotaxis extended to include other bioleaching microorganisms
and biofilm formation (Osorio et al. 2008a, b). Recently, work has begun to
elucidate mechanisms of copper resistance in A. ferroox-
Knowledge of the fundamental physical and biological idans (Navarro et al. 2009) and Ferroplasma acidarmanus
interactionsbetweenamicroorganismandamineralsurface Fer1usingcombinedgenomicandexperimentalapproaches
is central to understanding the intricacies of interfacial (Baker-Austin et al. 2005).
614 ApplMicrobiolBiotechnol(2010)88:605–620
Metabolic regulation this analysis incorporates a complete TCA cycle into the
proposed flux model, whereas it has been shown that A.
The study of gene regulation, including transcription factor ferrooxidans is more likely to have an incomplete TCA
characterization and promoter structure elucidation, has cycle(Valdésetal.2008b).Theeffectofthispossibleerror
been significantly improved by the availability of whole on the overall interpretation of the flux analysis has not
genome DNA sequences and the use of high throughput been determined.
methods to evaluate gene expression. However, current Itisexpectedthatwiththeincreasinggenomicdataand
discoveries are concentrated in model organisms like bioinformatic interpretation available, metabolic flux
Bacillus subtilis, Pseudomonas aeruginosa, and Escherichia analysis and other tools of metabolomics will assume
coli K-12, where large amounts of experimental data have increasingly important roles in helping to understand
been generated. The scenario is dramatically different for bioleaching.
many newly sequenced microorganisms, where limited
amounts of experimental data are available or, in some
cases, where they are difficult to manipulate in the Genome diversity
laboratory, as is the case for many extreme acidophiles.
Bioinformatic analysis of the genome data of A. Genomediversityacrossspeciesandgeneraisacriticalissue
ferrooxidans has been used to predict the regulation of to make a more precise interpretation of the metabolic
nitrogen metabolism (Barreto et al. 2003; Levican et al. potential of a natural microbial community. In the specific
2008), sulfur assimilation and its regulatory interplay with case of extreme acidophilic microbes, only a few species
nitrogen fixation, hydrogen oxidation and energy metabo- havebeenusedtoexploregenomediversityandthepotential
lism (Valdés et al. 2003), iron homeostasis (references in evolutionary processes responsible for this variation.
preceding paragraph), CO fixation (Esparza et al. 2009, Severalhighthroughputapproachescanbeusedtostudy
2
2010) and other aspects of central carbon metabolism population genomics and evolution in natural environ-
(Appia-Aymeetal.2006).Someofthesemodelshavebeen ments. The tools for these studies range from whole
supported with experimental evidence. genome sequencing of isolated representatives and the
Genome data of bioleaching microorganisms is begin- subsequent elaboration of specifically designed compara-
ning to be mined to identify and predict the role of small tivegenomehybridization (CGH) microarraystotheuseof
regulatoryRNAs(srRNAs)ingeneregulation(Shmaryahu metagenomic approaches for the generation of a picture of
and Holmes 2007). Also, preliminary investigations are the microbial diversity and predicted functional properties
beginning to reveal mechanisms involved in the regulation of an environmental sample.
ofFe(II)andSoxidationinA.ferrooxidans(Amouricetal. Genome sequencing followed by sequence interrogation
2009) including the possible use of a srRNA (Shmaryahu using specifically designed CGH microarrays has been
et al. 2009). carried out across a single phylogenetic branch of eight
The examples of regulatory models described provide strainsofThiomonastoevaluategenomevariation(Arsène-
some initial insights into the regulatory mechanisms and Ploetzeetal.2010).TheresultssuggestthattheThiomonas
dynamics operating in bioleaching and provide rudimen- genome has evolved through the gain or loss of genomic
tary models that help to explain some of the specific islands and that this evolution is influenced by the specific
adaptationsthatpromoteandsustainlifeinextremeacidic environmental conditions in which the strains live.
environments. Sequencing and analyses of three representatives of the
Acidithiobacillus genus (A. ferrooxidans, A. thiooxidans,
and A. caldus) have provided a snapshot of the main
Metabolic engineering functional differences that help shape the ecophysiology of
theextremeacidicandbiominingniches.Majordifferences
Metabolic engineering—the practice of manipulating the in gene content between the three species demonstrate that
genetic and regulatory processes within a cell in order to different branches of the Acidithiobacillus genus have
increase the production of a substance or to improve the evolved different strategies for the oxidation of reduced
activity of the organism for some process—has not been inorganic sulfur compounds (RISCs) and that some have
exploitedinanyextremeacidophile.Metabolicengineering specializedtocarryoutcritical metabolicprocessessuchas
requires at least a rough understanding of the metabolic iron oxidation and nitrogen fixation (Valdés et al. 2009;
fluxes within the cell in order to identify potential bottle- Valdés and Holmes 2009). In addition, a phylogenomic
necks in the reactions that can be manipulated by genetic approach based on gene family comparisons of the three
engineering.Onlyonesuchanalysishasbeenpublishedfor acidithiobacilli has identified a conserved genome core
an extreme acidophile (Hold et al. 2009). Unfortunately, inheritedfromtheircommonancestorandsetsofdispensable